{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1c917d9c910>]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib import pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import h5py\n",
    "from os import path\n",
    "from scipy.signal import windows\n",
    "M2 = 41\n",
    "std_p = 4\n",
    "std_s = 4\n",
    "w_p = windows.gaussian(M2, std_p)\n",
    "w_s = windows.gaussian(M2, std_s)\n",
    "w_p_small = windows.gaussian(M2, std_p/2)*0.8\n",
    "w_s_small = windows.gaussian(M2, std_s/2)*0.8\n",
    "\n",
    "npconcat = np.concatenate\n",
    "npzeros = np.zeros\n",
    "npones = np.ones\n",
    "\n",
    "def gen_gaussianlabel(p_arr, s_arr, width):\n",
    "    \"\"\"生成拾取标签，即在震相到达处是个高斯窗，其余位置全0\n",
    "\n",
    "    Args:\n",
    "        p_arr: P波到达采样点\n",
    "        s_arr: S波到达采样点\n",
    "        width: 数据长度\n",
    "\n",
    "    Returns:\n",
    "        三分量的高斯窗拾取标签\n",
    "    \"\"\"\n",
    "    l_p = int(p_arr-(M2-1)/2)\n",
    "    r_p = int(width-l_p-M2)    \n",
    "    l_s = int(s_arr-(M2-1)/2)\n",
    "    r_s = int(width-l_s-M2)\n",
    "    if(min(l_p,r_p,l_s,r_s)<0):\n",
    "        raise IndexError(\n",
    "            \"label position < 0:{} {} {} {} {} {}\".format(p_arr, s_arr, l_p, r_p, l_s, r_s))\n",
    "    if (s_arr-p_arr > M2/2):\n",
    "        # generate pick label\n",
    "        label_p2 = npzeros(width)\n",
    "        label_p2[l_p: l_p+M2]=w_p\n",
    "        label_s2 = npzeros(width)\n",
    "        label_s2[l_s: l_s+M2] = w_s\n",
    "        label_n2 = npones(width)-label_p2-label_s2\n",
    "    else:\n",
    "        # generate narrower pick label\n",
    "        label_p2 = npzeros(width)\n",
    "        label_p2[l_p: l_p+M2]=w_p_small\n",
    "        label_s2 = npzeros(width)\n",
    "        label_s2[l_s: l_s+M2] = w_s_small\n",
    "        label_n2 = npones(width)-label_p2-label_s2\n",
    "    return np.array([label_p2, label_s2, label_n2])\n",
    "\n",
    "plt.plot(gen_gaussianlabel(50,70,120)[0])\n",
    "plt.plot(gen_gaussianlabel(50,70,120)[1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# x = np.linspace(0, 40, 41)\n",
    "y = 1-np.abs(np.linspace(-1, 1, 41))\n",
    "# y=-y\n",
    "plt.plot(y)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\ProgramData\\Miniconda3\\lib\\site-packages\\tqdm\\auto.py:22: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2272 2522 2228\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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j65RByCAddPcygY2BgOiBMRAQkWZ0nTLQ6XROCwuJ6MEwEBCRZnSdMgDAyxcTqYiBgIg0o+uFiTp/8loERGphICAizeh6++POn52/wriGgOjBMRAQkWbY3I4QdP60cw0B0QNjICAizXBbQ6Dn/QyI1MJAQESa4T5l4LgFMgMB0YNiICAizXBfVMjTDonUwkBARJphc5kyMPC0QyLV9CoQ7Ny5E4mJiQgLC0NKSgo+++yzbtsXFxcjJSUFYWFhGD16NPLy8nrVWSIKbq5TBsp1CDhlQPTAfA4Ehw4dwpo1a7Bx40aUl5dj6tSpSE9PR01Njcf2VVVVmDt3LqZOnYry8nJkZWXhjTfeQH5+/gN3noiCi9uUgZ5rCIjU4nMg2LZtG1555RWsXLkS48aNQ25uLuLj47Fr1y6P7fPy8jBy5Ejk5uZi3LhxWLlyJV5++WVs3br1gTtPRMFFmTLQcw0Bkdr0vjS22Ww4e/Ys1q9f77Q9LS0NJSUlHvcpLS1FWlqa07bZs2djz549aGtrg8FgcNvHarXCarUqz5ubmwEALS0tvnTXq9tWOzI+OKvKexFR/7l7+1bnz1utaBnUBrHdQYf1Dv5vQQU+KL40wL0jUsfjsRHYOO8J1d7P8d0p0n1w9ikQ3LhxA+3t7YiJiXHaHhMTg/r6eo/71NfXe2xvt9tx48YNxMbGuu2Tk5ODzZs3u22Pj4/3pbtEFKB+mOv8vHZAekHUN44C+GMfvG9raytMJpPX130KBA46nc7puYi4beupvaftDhs2bEBmZqbyvKOjA//6178QFRXV7ef4oqWlBfHx8aitrUVkZKQq7znQWJM2BFpNgVYPwJq0gjXdHxFBa2sr4uLium3nUyAYPnw4QkJC3I4GNDQ0uB0FcDCbzR7b6/V6REVFedzHaDTCaDQ6bfvBD37gS1fvW2RkZMD8RXJgTdoQaDUFWj0Aa9IK1tSz7o4MOPi0qDA0NBQpKSkoLCx02l5YWIgpU6Z43Mdisbi1P378OFJTUz2uHyAiIqL+5/NZBpmZmdi9ezf27t2LS5cuYe3ataipqUFGRgaAzsP9y5YtU9pnZGSguroamZmZuHTpEvbu3Ys9e/Zg3bp16lVBRERED8TnNQSLFy9GY2Mj3n77bdTV1SEpKQkFBQVISEgAANTV1TldkyAxMREFBQVYu3YtduzYgbi4OGzfvh0vvPCCelX0gtFoRHZ2ttvUhJaxJm0ItJoCrR6ANWkFa1KXTno6D4GIiIgCHu9lQERERAwERERExEBAREREYCAgIiIiBGkg8PX2zQNp06ZN0Ol0Tg+z2ay8LiLYtGkT4uLiMHjwYEyfPh0XLlxweg+r1YrXX38dw4cPR3h4OJ577jl88803/VbDyZMnsWDBAsTFxUGn0+Gjjz5yel2tGm7evImlS5fCZDLBZDJh6dKlaGpq6vd6VqxY4TZmkydP9tt6gM7Lhf/oRz9CREQEoqOj8bOf/QyVlZVObbQ2TvdTk5bGateuXZg4caJywRqLxYJ//OMfyutaG5/7qUlL4+NNTk4OdDod1qxZo2zz27GSIHPw4EExGAzyl7/8RS5evCirV6+W8PBwqa6uHuiueZSdnS3jx4+Xuro65dHQ0KC8vmXLFomIiJD8/Hw5d+6cLF68WGJjY6WlpUVpk5GRIY888ogUFhZKWVmZzJgxQ5KTk8Vut/dLDQUFBbJx40bJz88XAHLkyBGn19WqYc6cOZKUlCQlJSVSUlIiSUlJMn/+/H6vZ/ny5TJnzhynMWtsbHRq40/1iIjMnj1b3nvvPTl//rxUVFTIvHnzZOTIkXLr1i2ljdbG6X5q0tJYHT16VI4dOyaVlZVSWVkpWVlZYjAY5Pz58yKivfG5n5q0ND6efPHFFzJq1CiZOHGirF69Wtnur2MVdIHg6aefloyMDKdtjz/+uKxfv36AetS97OxsSU5O9vhaR0eHmM1m2bJli7Lt7t27YjKZJC8vT0REmpqaxGAwyMGDB5U2V69elUGDBsnHH3/cp333xPULVK0aLl68KADk1KlTSpvS0lIBIF999VW/1SPS+Uvs+eef97qPP9fj0NDQIACkuLhYRLQ/Tp5qEtH+WA0dOlR2794dEOPjWpOItsentbVVHnvsMSksLJRp06YpgcCfxyqopgwct292vR1zd7dv9geXL19GXFwcEhMT8eKLL+Lrr78GAFRVVaG+vt6pHqPRiGnTpin1nD17Fm1tbU5t4uLikJSU5Bc1q1VDaWkpTCYTJk2apLSZPHkyTCbTgNRZVFSE6OhojBkzBq+++ioaGhqU17RQj+OW48OGDQMQGOPkWpODFseqvb0dBw8exO3bt2GxWAJifFxrctDi+ADAa6+9hnnz5uEnP/mJ03Z/Hqte3e1Qq3pz++aBNmnSJOzfvx9jxozBtWvX8M4772DKlCm4cOGC0mdP9VRXVwPovP10aGgohg4d6tbGH2pWq4b6+npER0e7vX90dHS/15meno5f/OIXSEhIQFVVFd566y3MnDkTZ8+ehdFo9Pt6RASZmZn48Y9/jKSkJKU/jj669lkL4+SpJkB7Y3Xu3DlYLBbcvXsXQ4YMwZEjR/DEE08oXwBaHB9vNQHaGx+HgwcPoqysDKdPn3Z7zZ//XwqqQODg6+2bB1J6erry5wkTJsBiseDRRx/F+++/ryyu6U09/lazGjV4aj8QdS5evFj5c1JSElJTU5GQkIBjx45h4cKFXvfzl3pWrVqFL7/8Ev/85z/dXtPqOHmrSWtjNXbsWFRUVKCpqQn5+flYvnw5iouLvfZDC+PjraYnnnhCc+MDALW1tVi9ejWOHz+OsLAwr+38cayCasqgN7dv9jfh4eGYMGECLl++rJxt0F09ZrMZNpsNN2/e9NpmIKlVg9lsxrVr19ze//r16wNeZ2xsLBISEnD58mUA/l3P66+/jqNHj+LEiRMYMWKEsl3L4+StJk/8faxCQ0Pxwx/+EKmpqcjJyUFycjL+9Kc/aXp8vNXkib+PD9B5uL+hoQEpKSnQ6/XQ6/UoLi7G9u3bodfrlc/0x7EKqkDQm9s3+xur1YpLly4hNjYWiYmJMJvNTvXYbDYUFxcr9aSkpMBgMDi1qaurw/nz5/2iZrVqsFgsaG5uxhdffKG0+fzzz9Hc3DzgdTY2NqK2thaxsbEA/LMeEcGqVatw+PBhfPrpp0hMTHR6XYvj1FNNnmhhrLoSEVitVk2OT081eaKF8Zk1axbOnTuHiooK5ZGamoolS5agoqICo0eP9t+x6tVSRA1znHa4Z88euXjxoqxZs0bCw8PlypUrA901j958800pKiqSr7/+Wk6dOiXz58+XiIgIpb9btmwRk8kkhw8flnPnzslLL73k8fSVESNGyCeffCJlZWUyc+bMfj3tsLW1VcrLy6W8vFwAyLZt26S8vFw51VOtGubMmSMTJ06U0tJSKS0tlQkTJvTJqUXd1dPa2ipvvvmmlJSUSFVVlZw4cUIsFos88sgjfluPiMhvf/tbMZlMUlRU5HSK1507d5Q2WhunnmrS2lht2LBBTp48KVVVVfLll19KVlaWDBo0SI4fPy4i2hufnmrS2vh0p+tZBiL+O1aaCATt7e1SW1srTU1N0tzc/MCPrVu3Snx8vBgMBklOTpaCggJV3rcvHgsXLpSYmBjR6/ViNptlwYIF8vnnnyuvNzU1yfr16yU6OlpCQ0NlypQpUlpa6vQe165dk9/85jcydOhQCQsLk9mzZ8uFCxf6rYa///3vAsDt8dJLL6laQ1VVlSxatEiGDBkiQ4YMkUWLFkl1dXW/1lNfXy8zZ86UqKgo0ev1MmLECHnppZfc+upP9TQ3N3usB4Ds3LlT9b9r/VVXTzVpbax+9atfKb+3oqKiZNq0aXLkyBHNjk9PNWltfLp7PPPMM5KRkTFgY9XU1CS1tbXS3t7e7XetJm5//M033yA+Pn6gu0FERKRZtbW13a6j0cRZBhEREQA6i4mMjBzg3hAREWlHS0sL4uPjle9SbzQRCBynUDiud01ERES+6el0xKA6y4CIiIg8YyAgIiIi3wNBT7d+9aS4uBgpKSkICwvD6NGjkZeX15u+EhERUR/xORDcvn0bycnJ+POf/3xf7auqqjB37lxMnToV5eXlyMrKwhtvvIH8/HyfO0tERER9w+dFhenp6U7X1+9JXl4eRo4cidzcXADAuHHjcObMGWzduhUvvPCCrx9PREREfaDP1xCUlpa63W549uzZOHPmDNra2vr644mIHsjVpu+ggcu1ED2wPg8E9fX1Hm/zaLfbcePGDY/7WK1WtLS0OD2IiPrbx+fr8MyWT7Gz6P8NdFeI+ly/nGXg6TaPnrY75OTkwGQyKQ9epZCIBsL/Ntxy+kkUyPo8EJjNZo+3edTr9YiKivK4z4YNG9Dc3Kw8amtr+7qbRERu2to7//Fia+8Y4J4Q9b0+v1KhxWLB3/72N6dtx48fR2pqKgwGg8d9jEYjjEZjX3eNiKhbbfeCQJudgYACn89HCG7duqXc4xnoPK2woqICNTU1ADr/db9s2TKlfUZGBqqrq5GZmYlLly5h79692LNnD9atW6dOBUREfUQJBDxCQEHA5yMEZ86cwYwZM5TnmZmZAIDly5dj3759qKurU8IBACQmJqKgoABr167Fjh07EBcXh+3bt/OUQyLye44pA3sHzzKgwOdzIJg+fXq3p+Ds27fPbdu0adNQVlbm60cREQ0ox5EBG6cMKAjwXgZERF5wyoCCCQMBEZEX9ntTBo6pA6JAxkBAROSFjUcIKIgwEBAReaGsIWAgoCDAQEBE5MX3UwYMBBT4GAiIiLxQpgzsXENAgY+BgIjIC55lQMGEgYCIyAs772VAQYSBgIjICx4hoGDCQEBE5IWN1yGgIMJAQETkhf3ekYH2DkE772dAAY6BgIjIi65TBZw2oEDHQEBE5EXXqQIGAgp0DARERF44HyHglAEFNgYCIiIvOGVAwYSBgIjIi65HBWx2BgIKbAwERERe2HiEgIIIAwERkRd2riGgIMJAQETkQXuHoOulB3iEgAIdAwERkQeuAYCBgAIdAwERkQfugYBTBhTYGAiIiDxwDQA8QkCBjoGAiMgD1wDAWyBToGMgICLywG3KgNchoADHQEBE5IH7lAHXEFBgYyAgIvKAZxlQsGEgICLygGsIKNgwEBARecCzDCjYMBAQEXnARYUUbBgIiIg84IWJKNgwEBAReeAaALiGgAIdAwERkQeuUwRcQ0CBjoGAiMgDewcDAQUXBgIiIg9svDARBRkGAiIiD1ynDGw8y4ACHAMBEZEHnDKgYMNAQETkgfuUAQMBBbZeBYKdO3ciMTERYWFhSElJwWeffea1bVFREXQ6ndvjq6++6nWniYj6mvtZBlxDQIHN50Bw6NAhrFmzBhs3bkR5eTmmTp2K9PR01NTUdLtfZWUl6urqlMdjjz3W604TEfU11ykDXoeAAp3PgWDbtm145ZVXsHLlSowbNw65ubmIj4/Hrl27ut0vOjoaZrNZeYSEhPS600REfc31iICdgYACnE+BwGaz4ezZs0hLS3PanpaWhpKSkm73ffLJJxEbG4tZs2bhxIkTvveUiKgfOc4qMOo7f01yyoACnd6Xxjdu3EB7eztiYmKctsfExKC+vt7jPrGxsXj33XeRkpICq9WKDz74ALNmzUJRURGeffZZj/tYrVZYrVbleUtLiy/dJCJ6YI4pg4dCQ2C1d3BRIQU8nwKBg06nc3ouIm7bHMaOHYuxY8cqzy0WC2pra7F161avgSAnJwebN2/uTdeIiFThOCLwUKgeN++08ToEFPB8mjIYPnw4QkJC3I4GNDQ0uB016M7kyZNx+fJlr69v2LABzc3NyqO2ttaXbhIRPTBHAAg3dq534hECCnQ+BYLQ0FCkpKSgsLDQaXthYSGmTJly3+9TXl6O2NhYr68bjUZERkY6PYiI+pNjymBwaOeBVK4hoEDn85RBZmYmli5ditTUVFgsFrz77ruoqalBRkYGgM5/3V+9ehX79+8HAOTm5mLUqFEYP348bDYbDhw4gPz8fOTn56tbCRGRitrsnQEgPJRHCCg4+BwIFi9ejMbGRrz99tuoq6tDUlISCgoKkJCQAACoq6tzuiaBzWbDunXrcPXqVQwePBjjx4/HsWPHMHfuXPWqICJSmSMAPHTvCAGvQ0CBTicifn8crKWlBSaTCc3NzZw+IKJ+8fpfy/G3//kWzyXH4ej/fIv4YYPx2e9mDnS3iHx2v9+hvJcBEZEHba6LCu1+/28nogfCQEBE5IHrlAHXEFCgYyAgIvKgrcNxHYLOIwRcQ0CBjoGAiMgDx5QBjxBQsGAgICLy4PspA8dph1xDQIGNgYCIyANHIBh8LxC0dwjaOxgKKHAxEBAReeA4IhAequ+yjdMGFLgYCIiIPFCmDO6ddth1G1EgYiAgIvJACQSGroGAUwYUuBgIiIg8cHz5Gw0hCBmku7eNRwgocDEQEBF54PjyN4ToYAjpDASOWyITBSIGAiIiD74PBINgCBnktI0oEDEQEBF5YL83ZWAIGYTQe4HAztMOKYAxEBAReWBzmjLo/FXJKQMKZAwEREQeOE0Z6LmokAIfAwERkYv2DoFjdsB5DQGnDChwMRAQEbnoeiTAEKJT1hDwCAEFMgYCIiIXzoHg+yMEvAUyBTIGAiIiF/YuUwOdgeDeGgIuKqQAxkBAROTCcYRgkA4IGaTjGgIKCgwEREQuHFMD+ntBIFTPNQQU+BgIiIhcOKYMHIsJuYaAggEDARGRi673MQAAPW9uREGAgYCIyIXrlIHBMWXARYUUwBgIiIhcuE4ZhHJRIQUBBgIiIheuUwbK7Y85ZUABjIGAiMiF25QBr1RIQYCBgIjIRddbH3f9yUBAgYyBgIjIheOLP/TeVMH31yHgGgIKXAwEREQu2tymDO6tIeBZBhTAGAiIiFy0KVMGjkWFnDKgwMdAQETk4vuzDLiGgIIHAwERkQvXQOC4DoGdawgogDEQEBG5cJ8y4HUIKPAxEBARuXCbMuDdDikIMBAQEbnwvoaAUwYUuBgIiIhcuE4ZhHJRIQWBXgWCnTt3IjExEWFhYUhJScFnn33Wbfvi4mKkpKQgLCwMo0ePRl5eXq86S0TUH7wdIeB1CCiQ+RwIDh06hDVr1mDjxo0oLy/H1KlTkZ6ejpqaGo/tq6qqMHfuXEydOhXl5eXIysrCG2+8gfz8/AfuPBFRX3APBDqn7USByOdAsG3bNrzyyitYuXIlxo0bh9zcXMTHx2PXrl0e2+fl5WHkyJHIzc3FuHHjsHLlSrz88svYunXrA3eeiKgv2F3PMuCliykI6H1pbLPZcPbsWaxfv95pe1paGkpKSjzuU1pairS0NKdts2fPxp49e9DW1gaDweC2j9VqhdVqVZ43NzcDAFpaWnzprle3rXZkfHBWlfciosDzzc076LDaYL97By0tLWi7cxsd1juorL2L57cVDnT3KMA9HhuBjfOeUO39HN+dIt0HWp8CwY0bN9De3o6YmBin7TExMaivr/e4T319vcf2drsdN27cQGxsrNs+OTk52Lx5s9v2+Ph4X7pLRPRANuUCm1y2XR6AflBwOQrgj33wvq2trTCZTF5f9ykQOOh0OqfnIuK2raf2nrY7bNiwAZmZmcrzjo4O/Otf/0JUVFS3n+OLlpYWxMfHo7a2FpGRkaq850BjTdoQaDUFWj0Aa9IK1nR/RAStra2Ii4vrtp1PgWD48OEICQlxOxrQ0NDgdhTAwWw2e2yv1+sRFRXlcR+j0Qij0ei07Qc/+IEvXb1vkZGRAfMXyYE1aUOg1RRo9QCsSStYU8+6OzLg4NOiwtDQUKSkpKCw0HkOrbCwEFOmTPG4j8VicWt//PhxpKamelw/QERERP3P57MMMjMzsXv3buzduxeXLl3C2rVrUVNTg4yMDACdh/uXLVumtM/IyEB1dTUyMzNx6dIl7N27F3v27MG6devUq4KIiIgeiM9rCBYvXozGxka8/fbbqKurQ1JSEgoKCpCQkAAAqKurc7omQWJiIgoKCrB27Vrs2LEDcXFx2L59O1544QX1qugFo9GI7Oxst6kJLWNN2hBoNQVaPQBr0grWpC6d9HQeAhEREQU83suAiIiIGAiIiIiIgYCIiIjAQEBEREQI0kDg6+2bB9KmTZug0+mcHmazWXldRLBp0ybExcVh8ODBmD59Oi5cuOD0HlarFa+//jqGDx+O8PBwPPfcc/jmm2/6rYaTJ09iwYIFiIuLg06nw0cffeT0ulo13Lx5E0uXLoXJZILJZMLSpUvR1NTU7/WsWLHCbcwmT57st/UAnZcL/9GPfoSIiAhER0fjZz/7GSorK53aaG2c7qcmLY3Vrl27MHHiROWCNRaLBf/4xz+U17U2PvdTk5bGx5ucnBzodDqsWbNG2ea3YyVB5uDBg2IwGOQvf/mLXLx4UVavXi3h4eFSXV090F3zKDs7W8aPHy91dXXKo6GhQXl9y5YtEhERIfn5+XLu3DlZvHixxMbGSktLi9ImIyNDHnnkESksLJSysjKZMWOGJCcni91u75caCgoKZOPGjZKfny8A5MiRI06vq1XDnDlzJCkpSUpKSqSkpESSkpJk/vz5/V7P8uXLZc6cOU5j1tjY6NTGn+oREZk9e7a89957cv78eamoqJB58+bJyJEj5datW0obrY3T/dSkpbE6evSoHDt2TCorK6WyslKysrLEYDDI+fPnRUR743M/NWlpfDz54osvZNSoUTJx4kRZvXq1st1fxyroAsHTTz8tGRkZTtsef/xxWb9+/QD1qHvZ2dmSnJzs8bWOjg4xm82yZcsWZdvdu3fFZDJJXl6eiIg0NTWJwWCQgwcPKm2uXr0qgwYNko8//rhP++6J6xeoWjVcvHhRAMipU6eUNqWlpQJAvvrqq36rR6Tzl9jzzz/vdR9/rsehoaFBAEhxcbGIaH+cPNUkov2xGjp0qOzevTsgxse1JhFtj09ra6s89thjUlhYKNOmTVMCgT+PVVBNGThu3+x6O+bubt/sDy5fvoy4uDgkJibixRdfxNdffw0AqKqqQn19vVM9RqMR06ZNU+o5e/Ys2tranNrExcUhKSnJL2pWq4bS0lKYTCZMmjRJaTN58mSYTKYBqbOoqAjR0dEYM2YMXn31VTQ0NCivaaEexy3Hhw0bBiAwxsm1JgctjlV7ezsOHjyI27dvw2KxBMT4uNbkoMXxAYDXXnsN8+bNw09+8hOn7f48Vr2626FW9eb2zQNt0qRJ2L9/P8aMGYNr167hnXfewZQpU3DhwgWlz57qqa6uBtB5++nQ0FAMHTrUrY0/1KxWDfX19YiOjnZ7/+jo6H6vMz09Hb/4xS+QkJCAqqoqvPXWW5g5cybOnj0Lo9Ho9/WICDIzM/HjH/8YSUlJSn8cfXTtsxbGyVNNgPbG6ty5c7BYLLh79y6GDBmCI0eO4IknnlC+ALQ4Pt5qArQ3Pg4HDx5EWVkZTp8+7faaP/+/FFSBwMHX2zcPpPT0dOXPEyZMgMViwaOPPor3339fWVzTm3r8rWY1avDUfiDqXLx4sfLnpKQkpKamIiEhAceOHcPChQu97ucv9axatQpffvkl/vnPf7q9ptVx8laT1sZq7NixqKioQFNTE/Lz87F8+XIUFxd77YcWxsdbTU888YTmxgcAamtrsXr1ahw/fhxhYWFe2/njWAXVlEFvbt/sb8LDwzFhwgRcvnxZOdugu3rMZjNsNhtu3rzptc1AUqsGs9mMa9euub3/9evXB7zO2NhYJCQk4PLlywD8u57XX38dR48exYkTJzBixAhlu5bHyVtNnvj7WIWGhuKHP/whUlNTkZOTg+TkZPzpT3/S9Ph4q8kTfx8foPNwf0NDA1JSUqDX66HX61FcXIzt27dDr9crn+mPYxVUgaA3t2/2N1arFZcuXUJsbCwSExNhNpud6rHZbCguLlbqSUlJgcFgcGpTV1eH8+fP+0XNatVgsVjQ3NyML774Qmnz+eefo7m5ecDrbGxsRG1tLWJjYwH4Zz0iglWrVuHw4cP49NNPkZiY6PS6Fsepp5o80cJYdSUisFqtmhyfnmryRAvjM2vWLJw7dw4VFRXKIzU1FUuWLEFFRQVGjx7tv2PVq6WIGuY47XDPnj1y8eJFWbNmjYSHh8uVK1cGumsevfnmm1JUVCRff/21nDp1SubPny8RERFKf7ds2SImk0kOHz4s586dk5deesnj6SsjRoyQTz75RMrKymTmzJn9etpha2urlJeXS3l5uQCQbdu2SXl5uXKqp1o1zJkzRyZOnCilpaVSWloqEyZM6JNTi7qrp7W1Vd58800pKSmRqqoqOXHihFgsFnnkkUf8th4Rkd/+9rdiMpmkqKjI6RSvO3fuKG20Nk491aS1sdqwYYOcPHlSqqqq5Msvv5SsrCwZNGiQHD9+XES0Nz491aS18elO17MMRPx3rIIuEIiI7NixQxISEiQ0NFSeeuopp9OQ/I3j/FSDwSBxcXGycOFCuXDhgvJ6R0eHZGdni9lsFqPRKM8++6ycO3fO6T2+++47WbVqlQwbNkwGDx4s8+fPl5qamn6r4cSJEwLA7bF8+XJVa2hsbJQlS5ZIRESEREREyJIlS+TmzZv9Ws+dO3ckLS1NHn74YTEYDDJy5EhZvny5W1/9qR4R8VgPAHnvvfeUNlobp55q0tpYvfzyy8rvrYcfflhmzZqlhAER7Y1PTzVpbXy64xoI/HWsePtjIiIiCq41BEREROQZAwERERExEBAREREDAREREYGBgIiIiMBAQERERGAgICIiIjAQEBERERgIiIiICAwEREREBAYCIiIiAgMBERERAfj/ODHvc58ibxAAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 600x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from dataset import crop_data,gen_trilabel\n",
    "from utils import *\n",
    "\n",
    "parr=4500\n",
    "sarr=4750\n",
    "label=gen_gaussianlabel(parr,sarr,9000)\n",
    "label_crop, p_arr, s_arr, wstart = crop_data(label,parr,sarr)\n",
    "print(p_arr, s_arr, wstart)\n",
    "# plot_ps(label)\n",
    "plot_ps(label_crop)\n",
    "tri_label=gen_trilabel(p_arr,s_arr,label_crop.shape[1])\n",
    "plot_ps(tri_label)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(3, 9000)\n",
      "[-0.70779848 -0.70779848 -0.70779848 ... -0.70779848 -0.70779848\n",
      " -0.70779848]\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x300 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ml=preprocess(label)\n",
    "print(ml.shape)\n",
    "print(ml[0])\n",
    "plot3C(ml)"
   ]
  }
 ],
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